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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # (Senior) Data Scientist (all genders) - **Company:** Flaconi GmbH - **Location:** Berlin, Germany (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Microsoft Azure, Big Data, Cluster Analysis, Programming Tools, Distributed Computing Environment, Github, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Recommender Systems, Tensorflow, Azure Machine Learning, SQL Databases, Feature Engineering, Pytorch, Prophet, Transfer Learning, Random Forest, Apache Spark, Deep Learning, Generative AI, Keras, Pandas, Matplotlib, AI Platforms, Pyspark, Core Data, Scikit Learn, Xgboost, Machine Learning Operations, Data Lakehouse, Virtual Agents, Functional Programming, GPT, Recurrent Neural Networks, Databricks - **Published:** August 28, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=1b7c8eb756609e65 ## About the Role * Bring a minimum of 3 years of hands-on experience in developing and deploying machine learning solutions for real-world business problems. * Demonstrate background exposure to e-commerce (ideal), fintech, or fast-paced agency environments. * Demonstrate hands-on experience with Databricks as a Data & AI platform (required) alongside cloud platforms such as AWS, GCP, or Azure. * Prove hands-on experience in building, productionalizing, and deploying Generative AI or Agentic AI solutions. * Apply hands-on experience with MLOps practices and tools (required) for end-to-end model lifecycle management. * Possess a strong grasp of core data science principles to select the most appropriate techniques, combined with advanced proficiency in SQL, Python (PySpark, scikit-learn, NumPy, matplotlib, pandas), and AI-augmented development tools (Claude, Copilot). * Communicate exceptionally in English (written and verbal) to articulate complex concepts to non-technical stakeholders, driving projects with full end-to-end ownership as a collaborative team player. ## Description We are seeking a (Senior) Data Scientist (all genders) to join a dynamic team of six within our DATA department. You'll dive into diverse challenges including training and deploying machine learning models, developing Generative AI and Agentic AI solutions, and statistical modeling. We believe in flat hierarchies, which means you'll work closely with colleagues of various seniorities in a fun environment. You'll play a key role in extracting valuable insights and developing data and AI solutions to optimize our e-commerce platform across Europe, taking end-to-end ownership of your projects and collaborating closely with business stakeholders along the way. Your contributions will have a direct impact on business decisions and process efficiency across a wide spectrum of unique use cases. Your Role * Employ statistical techniques and machine learning algorithms for regression, classification, and clustering (e.g., Gradient Boosting, Random Forest, Hierarchical Clustering, ensemble methods). * Develop and productionalize Generative AI and Agentic AI solutions alongside modern NLP techniques using transformer architectures (e.g., BERT, GPT). * Utilize time-series forecasting methods (e.g., ARIMA, LSTM, DeepAR, Prophet) for predictive modeling. * Conduct exploratory data analysis (EDA), advanced feature engineering, and dimensionality reduction (PCA, t-SNE). * Develop and implement deep learning models in PyTorch, TensorFlow, or Keras while leveraging transfer learning strategies. * Showcase your skills across key e-commerce data science use cases including demand forecasting, churn and CLTV modeling, pricing, customer segmentation, recommender systems, and personalization. * Handle large-scale datasets using distributed computing frameworks (Apache Spark) on a tech stack comprising Python (PySpark, pandas, NumPy, scikit-learn, LightGBM), SQL, Databricks (Data Lakehouse & ML platform), AWS (S3, Lambda, EC2, SageMaker, Bedrock), GitHub, and AI-augmented tools (Claude, Copilot) while collaborating directly to proactively address stakeholder business needs. ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Vectorize all the things! 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